Varicella zoster virus (VZV) is a herpesvirus that causes chickenpox and shingles. The biological mechanisms underpinning the multi-decadal latency of VZV in the body and subsequent viral reactivation-which occurs in approximately 30% of individuals-are largely unknown. Because chickenpox and shingles are endemic worldwide, understanding the relationship between VZV transmission and reactivation is important for informing disease treatment and control. While chickenpox is a vaccine-preventable childhood disease with a rich legacy of research, shingles is not a notifiable disease in most countries. To date, population-level studies of shingles have had to rely on small-scale hospital or community-level datasets. Here, we examined chickenpox and shingles notifications from Thailand and found strong seasonal incidence in both diseases, with a 3-month lag between peak chickenpox transmission season and peak shingles reactivation. We tested and fit 14 mathematical models examining the biological driversof chickenpox and shingles over an 8-year period to estimate rates of VZV transmission, reactivation, and immunity boosting, wherein re-exposure to VZV boosts VZV-specific immunity to reinforce protection against shingles. The models suggested the seasonal cycles of chickenpox and shingles have different underlying mechanisms, with ultraviolet radiation (UV) being correlated with shingles reactivation.Chromatin structures (and modulators thereof) play a central role in genome organization and function. Herein, we report that thymine DNA glycosylase (TDG), an essential enzyme involved in DNA repair and demethylation, has the capacity to alter chromatin structure directly through its physical interactions with DNA. Using chemically defined nucleosome arrays, we demonstrate that TDG induces decompaction of individual chromatin fibers upon binding and promotes self-association of nucleosome arrays into higher-order oligomeric structures (i.e. condensation). Chromatin condensation is mediated by TDG's disordered polycationic N-terminal domain, whereas its C-terminal domain antagonizes this process. Furthermore, we demonstrate that TDG-mediated chromatin condensation is reversible by growth arrest and DNA damage 45 alpha (GADD45a), implying that TDG cooperates with its binding partners to dynamically control chromatin architecture. Finally, we show that chromatin condensation by TDG is sensitive to the methylation status of the underlying DNA. This new paradigm for TDG has specific implications for associated processes, such as DNA repair, DNA demethylation, and transcription, and general implications for the role of DNA modification 'readers' in controlling chromatin organization.Increasing fertility and decreasing mortality are major response strategies in Russian demographic reform, which has led to significant decreases in both abortion rate (AR) and infant mortality. This study explores mechanisms influencing the socioeconomic conditions leading to abortion and infant mortality. Spatial panel economic analysis using data from the 83 regions of the country covering four time periods was applied. Every 1000 USD increase in per capita gross regional product (GRP) can lead to a decrease of the AR by 0.075, while one year life expectancy increase would lower it by 0.441. For infant mortality rate (IMR), GRP also shows a positive impact, particularly in recent years, while the population size of the region has a negative impact. Every 1000 USD increase in per capita GRP would result in a rate decrease of 0.064 in IMR, and every increase of 1000 added population would lead to an increased IMR by 2.05. The harvest effect between AR and infant mortality that was evident earlier, but not in the recent years, implies that the health care system in Russia is effective. A comprehensive improvement in wellbeing, income, etc. can contribute to mitigation of abortion and infant mortality. Theoretically, this study extends current research by comprehensively displaying the spatio-temporal patterns of abortion and infant mortality in Russia and qualifies the impact of regional socioeconomic disparities with regard to these two issues.The aim of this study was to assess the role of climate variability on the incidence of dengue fever (DF), an endemic arboviral infection existing in Jakarta, Indonesia.  https://www.selleckchem.com/products/ldc203974-imt1b.html  The work carried out included analysis of the spatial distribution of confirmed DF cases from January 2007 to December 2018 characterising the sociodemographical and ecological factors in DF high-risk areas. Spearman's rank correlation was used to examine the relationship between DF incidence and climatic factors. Spatial clustering and hotspots of DF were examined using global Moran's I statistic and the local indicator for spatial association analysis. Classification and regression tree (CART) analysis was performed to compare and identify demographical and socio-ecological characteristics of the identified hotspots and low-risk clusters. The seasonality of DF incidence was correlated with precipitation (r=0.254, P less then 0.01), humidity (r=0.340, P less then 0.01), dipole mode index (r= -0.459, P less then 0.01) and Tmin (r= -0.181, P less then 0.05). DF incidence was spatially clustered at the village level (I=0.294, P less then 0.001) and 22 hotspots were identified with a concentration in the central and eastern parts of Jakarta. CART analysis showed that age and occupation were the most important factors explaining DF clustering. Areaspecific and population-targeted interventions are needed to improve the situation among those living in the identified DF high-risk areas in Jakarta.The transition from the control phase to elimination of malaria in China through the national malaria elimination programme has focussed attention on the need for improvement of the surveillance- response systems. It is now understood that routine passive surveillance is inadequate in the parasite elimination phase that requires supplementation by active surveillance in foci where cluster cases have occurred. This study aims to explore the spatial clusters and temporal trends of malaria cases by the multivariate auto-regressive state-space model (MARSS) along the border to Myanmar in southern China. Data for indigenous cases spanning the period from 2007 to 2010 were extracted from the China's Infectious Diseases Information Reporting Management System (IDIRMS). The best MARSS model indicated that malaria transmission in the study area during 36 months could be grouped into three clusters. The estimation of malaria transmission patterns showed a downward trend across all clusters. The proposed methodology used in this study offers a simple and rapid, yet effective way to categorize patterns of foci which provide assistance for active monitoring of malaria in the elimination phase.